Certified DoD AI Ethics Officer (CDIAEO)

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Length: 2 Days

Certified DoD AI Ethics Officer (CDIAEO) Certification Program by Tonex

Certified DoD  AI Ethics Officer (CDIAEO) is a two-day intensive certification program designed to equip defense personnel, AI practitioners, policymakers, and system engineers with the knowledge and practical skills necessary to develop, deploy, and govern AI technologies ethically in military applications. Based on the five ethical principles outlined by the Defense Innovation Board (DIB), this certification provides a structured approach to Responsible, Equitable, Traceable, Reliable, and Governable AI for defense operations.

Participants will explore real-world case studies, hands-on exercises, and policy applications to understand how these principles ensure fair, transparent, and accountable AI usage within the Department of Defense (DoD). The program also covers AI risk management, compliance frameworks, governance strategies, and bias mitigation techniques, ensuring that AI technologies align with national security interests while minimizing unintended consequences.

Upon successful completion of the course and final assessment, participants will receive the DoD AI Ethics Certification, demonstrating their ability to apply ethical AI principles to defense applications and ensuring compliance with DoD AI governance frameworks.

Learning Outcomes:

By the end of this certification, participants will be able to:

  • Understand the DoD AI Ethical Principles and their application in military AI systems.
  • Develop and assess AI technologies with responsibility, fairness, traceability, reliability, and governability in mind.
  • Identify and mitigate bias in AI models used for defense applications.
  • Apply DoD-approved AI risk management and compliance frameworks.
  • Evaluate and improve AI reliability and safety measures.
  • Participate in governance and oversight of AI programs in defense environments.
  • Mitigate unintended bias in AI models and ensure fairness in decision-making
  • Implement traceability through transparent documentation and audit processes
  • Assess AI reliability and lifecycle risks, ensuring system safety and effectiveness
  • Develop governable AI capabilities, incorporating fail-safes and oversight mechanisms
  • Navigate DoD AI governance frameworks and compliance regulations
  • Enhance decision-making processes by integrating AI ethics into DoD policies and acquisition

Target Audience

This certification is ideal for:

  • DoD personnel and policymakers involved in AI adoption and governance
  • AI and ML developers working on DoD AI projects
  • Defense contractors developing AI-enabled defense systems
  • System and software engineers integrating AI into military technologies
  • Ethics officers and compliance professionals overseeing AI policy adherence
  • Acquisition and procurement officials evaluating AI systems for DoD use
  • Military strategists and operations officers implementing AI for defense applications
  • Cybersecurity and risk management professionals assessing AI threats and vulnerabilities

Certification Level: Foundational to Intermediate

Delivery Mode: In-person or virtual

Day 1: Foundations and Principles of Ethical AI in DoD

Module 1: Introduction to AI Ethics in Defense (1.5 hours)

  • Overview of Artificial Intelligence in DoD
  • The role of AI ethics in national security and military operations
  • Defense Innovation Board (DIB) and the evolution of DoD AI Ethics Principles
  • AI-related policies, executive orders, and DoD AI Strategy

Module 2: Principle of Responsible AI (2 hours)

  • Definition and importance of responsibility in AI
  • Case studies of responsible AI failures and lessons learned
  • Role of human judgment and accountability in AI deployment
  • Framework for ensuring responsible AI development and use

Workshop:

  • Scenario-based discussion on ethical decision-making in AI deployment
  • Identifying responsible AI governance structures within DoD

Module 3: Principle of Equitable AI (1.5 hours)

  • Understanding bias in AI: sources and mitigation strategies
  • Bias detection techniques in machine learning models
  • Ensuring equity in AI systems through data governance
  • DoD policies on fairness and inclusivity in AI

Hands-on Exercise:

  • Bias detection and mitigation in a sample AI model
  • Analyzing real-world AI equity failures in defense and security

Module 4: Principle of Traceable AI (2 hours)

  • Importance of explainability, transparency, and auditability
  • Best practices for AI documentation and traceability in DoD projects
  • Understanding AI black-box models and interpretability tools
  • Compliance with AI standards and regulatory frameworks

Case Study Review:

  • Analysis of DoD AI systems with strong/weak traceability
  • Group discussion on improving traceability in defense AI programs

Day 2: Ensuring Reliable and Governable AI in DoD Operations

Module 5: Principle of Reliable AI (2 hours)

  • Ensuring AI reliability across mission-critical applications
  • AI testing, verification, and validation methodologies
  • DoD-specific risk management strategies for AI reliability
  • Lifecycle considerations for AI deployment

Hands-on Workshop:

  • Risk assessment exercise: Evaluating the reliability of AI-powered defense applications

Module 6: Principle of Governable AI (2 hours)

  • Defining governability in AI: From design to deployment
  • AI safety measures: Fail-safes, disengagement mechanisms, and override capabilities
  • Ethical red-teaming: Anticipating unintended AI behavior
  • Governance frameworks for AI oversight and compliance

Simulation Exercise:

  • AI failure response simulation: Managing unintended AI behavior in operational environments

Module 7: AI Ethics Policy, Compliance, and Future Trends (1.5 hours)

  • DoD AI governance framework and compliance measures
  • AI ethics and international military partnerships
  • Emerging trends in ethical AI development
  • Integrating AI ethics in DoD acquisition processes

Certification Exam Details

Exam Format:

  • Number of Questions: 50
  • Question Types: Multiple-choice and scenario-based questions
  • Exam Duration: 90 minutes
  • Passing Score: 80% (40 out of 50 correct answers required)
  • Exam Mode: Online (proctored) or in-person at DoD training centers

Exam Domains & Weighting

Domain Description Weight (%) Number of Questions
Responsible AI Ensuring accountability, ethical decision-making, and human oversight in AI development and deployment. 20% 10
Equitable AI Identifying and mitigating bias in AI models, ensuring fairness in defense applications. 20% 10
Traceable AI Ensuring AI systems are transparent, auditable, and properly documented for ethical deployment. 20% 10
Reliable AI Developing AI models that are safe, secure, and effective for DoD use across their lifecycle. 20% 10
Governable AI Implementing oversight, fail-safes, and response strategies for unintended AI behavior. 20% 10

 

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